strange output in comparison of float with float literal
This happens because in your statement
if(f == 0.7)
the 0.7 is treated as a double. Try 0.7f to ensure the value is treated as a float:
if(f == 0.7f)
But as Michael suggested in the comments below you should never test for exact equality of floating-point values.
Strange output when comparing same float values?
Floating point numbers are never accurate.
This statement is wrong. Some floating point numbers are accurate, such as 1.0, 12345.0, 12345.5, -2.25. All these numbers can be represented as integers didived by a power of 2. All numbers that cannot also are not accurate.
In your specific case,
float x = 0.5 results in
x having the value
1.00000000 * 2^-1. When you compare this against
double 0.5, both operands are converted to
double, so the comparison becomes
1.000000000000000 * 2^-1 == 1.000000000000000 * 2^-1, which succeeds.
float x = 0.1, it looks different. The value is stored as
1.01010101 * 2^-3 (or similar). Note that this is already not precise. When you compare this against
double 0.1, the float is extended with zeros at the end, the comparison becomes
1.010101010000000 * 2^-3 == 1.010101010101010 * 2^-3, which fails.
C : Strange error when using float and double [duplicate]
No guarantee that the result will be false and true, but the basic idea is pretty simple:
3.4 has type double. When you assign it to a
float, it'll get rounded. When you compare, that rounded number will be promoted back to a double, not necessarily the same double as
In the second case, everything's double throughout.
Why is the Output of This code , BYE.. and not HI [duplicate]
floating points numbers cannot be represented precisely. so you cannot equate two float directly. it differs normally with epsilon.
if(fabs(floatVarialbe-expectedValue) < **FLT_EPSILON**)
//statements to execute if they are equal
you should fabs function to get absolute value [remove negative sign], its defined in math.h library.
FLT_EPSILON is a relative error and its defined in float.h library
Due to rounding errors, most floating-point numbers end up being
slightly imprecise. As long as this imprecision stays small, it can
usually be ignored. However, it also means that numbers expected to be
equal (e.g. when calculating the same result through different correct
methods) often differ slightly, and a simple equality test fails.
if you want to know more, What Every Computer Scientist Should Know About Floating-Point Arithmetic
Why is there no output for this program? [duplicate]
Computers only store digital information. Integers can be represented accurately in binary, but floating point numbers are approximated.
It seems that in the approximations, additional tiny values are preventing your exact comparison from being true.
Now is a good time to google "what every programmer should know about floating point numbers" and read it. It will save you countless hours of future programming and debugging if you learn it early.
In addition, there are two floating point types "float" and "double". You are comparing a float to a double, so the approximations of the value are likely not the same approximation, creating more of a chance that the two values won't be equal.
comparing float values with double resulting different behaviour [duplicate]
x == 0.1
0.1 is not of type
float but of type
double don't have the same precision.
0.1f is of type
Why it works with
0.5 is because
0.5 has an exact representation in both
double (in binary IEEE-754) types.